A Level Psychology OCR Practice Exam

The Chi-squared test is appropriate for analyzing the difference between two or more independent groups when the data is nominal. Nominal data refers to categorical data without a specific order, such as gender, color preference, or types of pets. The Chi-squared test assesses whether the frequency distribution of the categories differs significantly between the groups.

This test compares the observed frequencies with the expected frequencies, assuming no difference between the groups. By doing so, it provides insights into whether any observed differences in counts or proportions are statistically significant.

In contrast, the other tests listed are suitable for different types of data or designs. The Mann-Whitney test is used for ordinal or continuous data that is not normally distributed, ANOVA is designed for comparing means from three or more groups of continuous data, and the Wilcoxon test is a non-parametric alternative for paired samples, not independent groups. Hence, the Chi-squared test is the most fitting choice for the scenario described.